search

tufts-ml / ml-research-reading-lists

Useful Reading Lists on topics of active research (PI: Mike Hughes)
MIT License
0 stars 1 forks source link

Variational inference for mixtures, topics, and sequences #4

Open michaelchughes opened 5 years ago

michaelchughes commented 5 years ago

Basics: KMeans and Mixture Models

K-means algorithm Sec. 9.1 of Bishop PRML http://research.microsoft.com/en-us/um/people/cmbishop/prml/

Gaussian mixture models and the EM algorithm Sec. 9.2 of Bishop PRML http://research.microsoft.com/en-us/um/people/cmbishop/prml/

Example stand-alone code (in Matlab and Python) https://github.com/michaelchughes/compare-matlab-numpy

Connections between mixture models and EM Sec. 9.3 of Bishop PRML

Bernoulli mixture models and the EM algorithm Sec. 9.3.3 of Bishop PRML

Markovian sequence models (HMMs, etc)

Markov chains review http://cs.brown.edu/courses/csci1420/recitations/MarkovChains.pdf

Dynamic programming review

http://cs.brown.edu/courses/csci1420/recitations/dynamicProgrammingWithStringKernels.pdf

HMMs See Chapter in Bishop

hzhz2020 commented 5 years ago

Are these two links no longer valid? http://cs.brown.edu/courses/csci1420/recitations/MarkovChains.pdf http://cs.brown.edu/courses/csci1420/recitations/dynamicProgrammingWithStringKernels.pdf

michaelchughes commented 5 years ago

Yeah unfortunately I don't have access to those URLS. Will try to dig up those resources from my old laptops....